It's useful when one is interested in P(X<x) and
expression on the right side begin to lose precision. This
function have default implementation but implementors are
encouraged to provide more precise implementation.

Type class for distributions with entropy, meaning Shannon entropy
in the case of a discrete distribution, or differential entropy in the
case of a continuous one. maybeEntropy should return Nothing if
entropy is undefined for the chosen parameter values.

Type class for distributions with entropy, meaning Shannon
entropy in the case of a discrete distribution, or differential
entropy in the case of a continuous one. If the distribution has
well-defined entropy for all valid parameter values then it
should be an instance of this type class.

This method uses a combination of Newton-Raphson iteration and
bisection with the given guess as a starting point. The upper and
lower bounds specify the interval in which the probability
distribution reaches the value p.